Model comparison
Gemini 3.7 Flash vs GPT-6 Sol
Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 49.2 on the Noometry Index.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. Gemini 3.7 Flash scores higher in 7 categories and GPT-6 Sol in 3 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Gemini 3.7 Flash leads 69.5 to 35.8.
- The biggest single-benchmark swing is Furniture Assembly: 26.7% for Gemini 3.7 Flash and 58.3% for GPT-6 Sol.
- Gemini 3.7 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol accepts more context: 1.05M tokens versus 1.05M.
Side by side
| Gemini 3.7 Flash | GPT-6 Sol | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 59.8 | 49.2 |
| Released | 2026-08-13 | 2026-09-22 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.75 | $2 |
| Output $ / M tokens | $3.75 | $10 |
| Results tracked | 44 | 22 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-6 Sol leads
Gemini 3.7 Flash: 55.7 (#19), GPT-6 Sol: 59.6 (#11)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| DeepSWE | 65.5% | 68.8% |
| FrontierCode | 43.6% | 49.3% |
| LMArena WebDev | 1593 | 1692 |
| LMArena Coding | 1499 | 1453 |
| FrontierSWE | 20.3% | — |
| SciCode | 59.8% | — |
| ALE-Bench | 904.3 | — |
Agentic & Tool Use Gemini 3.7 Flash leads
Gemini 3.7 Flash: 42.2 (#18), GPT-6 Sol: 33.5 (#49)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| GDP.pdf | 23.8% | 28% |
| APEX-Agents | 67.8% | — |
| Remote Labor Index | 5% | — |
Reasoning Gemini 3.7 Flash leads
Gemini 3.7 Flash: 70.1 (#12), GPT-6 Sol: 49.3 (#34)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| NYT Connections (extended) | 94% | 90.1% |
| LMArena Hard Prompts | 1497 | 1420 |
| ARC-AGI-2 | 84.6% | — |
| ARC-AGI-1 | 95.5% | — |
| CritPt | 14.3% | — |
| Chess Puzzles | 47% | — |
| EBR-Bench | — | 53.3% |
| Mystery Game Puzzles | 37% | — |
| DTBench | 96.8% | — |
| LMCA | 50.4% | — |
| Epoch Capabilities Index | 157.72 | — |
Math Gemini 3.7 Flash leads
Gemini 3.7 Flash: 69.5 (#18), GPT-6 Sol: 35.8 (#135)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| LMArena Math | 1511 | 1404 |
| FrontierMath (Tiers 1-3) | 71.6% | — |
| FrontierMath Tier 4 | 36.6% | — |
| OTIS Mock AIME 2024-2025 | 97.2% | — |
| ProofBench | 58% | — |
Knowledge Gemini 3.7 Flash leads
Gemini 3.7 Flash: 69.8 (#4), GPT-6 Sol: 43.0 (#87)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| LMArena Expert | 1508 | 1449 |
| GPQA Diamond | 94.8% | — |
| SimpleQA Verified | 69.2% | — |
| Vectara Hallucination Rate | — | 6.5% |
Multimodal GPT-6 Sol leads
Gemini 3.7 Flash: 36.9 (#69), GPT-6 Sol: 47.6 (#9)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| Furniture Assembly | 26.7% | 58.3% |
| LMArena Vision | 1314 | — |
Multilingual Gemini 3.7 Flash leads
Gemini 3.7 Flash: 57.8 (#7), GPT-6 Sol: 51.0 (#113)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| LMArena Non-English | 1485 | 1389 |
| LMArena Chinese | 1553 | 1416 |
| LMArena Russian | 1519 | 1407 |
| LMArena Spanish | 1507 | 1377 |
| LMArena French | 1512 | — |
| LMArena German | 1485 | — |
| LMArena Japanese | 1506 | — |
| LMArena Korean | 1486 | — |
Instruction Following Gemini 3.7 Flash leads
Gemini 3.7 Flash: 78.0 (#12), GPT-6 Sol: 74.4 (#97)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| LMArena Instruction Following | 1486 | 1406 |
Long Context Gemini 3.7 Flash leads
Gemini 3.7 Flash: 45.8 (#28), GPT-6 Sol: 43.2 (#100)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| LMArena Longer Query | 1493 | 1415 |
Writing & Preference Too close to call
Gemini 3.7 Flash: 71.4 (#19), GPT-6 Sol: 72.3 (#15)
| Benchmark | Gemini 3.7 Flash | GPT-6 Sol |
|---|---|---|
| LMArena Text | 1487 | 1396 |
| LMArena Creative Writing | 1490 | 1392 |
| EQ-Bench Creative Writing | 1723 | 2125 |
| LMArena Multi-Turn | 1495 | 1405 |
Frequently asked questions
Is Gemini 3.7 Flash better than GPT-6 Sol?
Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 49.2 on the Noometry Index.
Which is cheaper, Gemini 3.7 Flash or GPT-6 Sol?
Gemini 3.7 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GPT-6 Sol lists at $2 and $10.
Is Gemini 3.7 Flash or GPT-6 Sol better for coding?
GPT-6 Sol scores higher on coding benchmarks: 59.6 versus 55.7 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Sol does, with 1.05M tokens against 1.05M.
How many benchmarks do Gemini 3.7 Flash and GPT-6 Sol share?
20 benchmarks have published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and GPT-6 Sol has 22.